Adam Tauman Kalai

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All published works

Action	Title	Year	Authors
+ PDF Chat	OpenAI o1 System Card	2024	OpenAI NULL AUTHOR_ID Aaron Jaech Adam Tauman Kalai Adam Lerer Adam J. Richardson Ahmed El-Kishky A. M. Low Alec Helyar Aleksander Mądry
+	Calibrated Language Models Must Hallucinate	2024	Adam Tauman Kalai Santosh Vempala
+	Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding	2024	Mirac Süzgün Adam Tauman Kalai
+ PDF Chat	Social norm bias: residual harms of fairness-aware algorithms	2023	Myra Cheng Maria De‐Arteaga Lester Mackey Adam Tauman Kalai
+	Loss Minimization Yields Multicalibration for Large Neural Networks	2023	Jarosław Błasiok Parikshit Gopalan Lunjia Hu Adam Tauman Kalai Preetum Nakkiran
+	Do Language Models Know When They're Hallucinating References?	2023	Ayush Agrawal Lester Mackey Adam Tauman Kalai
+	Textbooks Are All You Need	2023	Suriya Gunasekar Yi Zhang Jyoti Aneja Caio César Teodoro Mendes Allie Del Giorno Sivakanth Gopi Mojan Javaheripi Piero Kauffmann Gustavo de Rosa Olli Saarikivi
+	Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation	2023	Eric Zelikman Eliana Lorch Lester Mackey Adam Tauman Kalai
+	Testing Language Model Agents Safely in the Wild	2023	Silen Naihin David Atkinson Marc Green Merwane Hamadi Craig Swift Douglas Schonholtz Adam Tauman Kalai David Bau
+	Calibrated Language Models Must Hallucinate	2023	Adam Tauman Kalai Santosh Vempala
+	Why GANs are overkill for NLP	2022	David Alvarez-Melis Vikas Garg Adam Tauman Kalai
+	Language Models Can Teach Themselves to Program Better	2022	Patrick Haluptzok Matthew R. Bowers Adam Tauman Kalai
+	Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies	2022	Gati Aher Rosa I. Arriaga Adam Tauman Kalai
+	Partial Matrix Completion	2022	Varun Kanade Elad Hazan Adam Tauman Kalai
+	Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms	2022	Surbhi Goel Sham M. Kakade Adam Tauman Kalai Cyril Zhang
+	A Theory of Unsupervised Translation Motivated by Understanding Animal Communication	2022	Shafi Goldwasser David F. Gruber Adam Tauman Kalai Orr Paradise
+	Towards optimally abstaining from prediction with OOD test examples.	2021	Adam Tauman Kalai Varun Kanade
+	Programming Puzzles	2021	Tal Schuster Ashwin Kalyan Oleksandr Polozov Adam Tauman Kalai
+	Towards optimally abstaining from prediction.	2021	Adam Tauman Kalai Varun Kanade
+	Efficient Learning with Arbitrary Covariate Shift	2021	Adam Tauman Kalai Varun Kanade
+	Efficient learning with arbitrary covariate shift	2021	Adam Tauman Kalai Varun Kanade
+	Social Norm Bias: Residual Harms of Fairness-Aware Algorithms	2021	Myra Cheng Maria De‐Arteaga Lester Mackey Adam Tauman Kalai
+	Towards optimally abstaining from prediction with OOD test examples	2021	Adam Tauman Kalai Varun Kanade
+	Efficient Learning with Arbitrary Covariate Shift	2021	Adam Tauman Kalai Varun Kanade
+	Programming Puzzles	2021	Tal Schuster Ashwin Kalyan Oleksandr Polozov Adam Tauman Kalai
+	Omnipredictors	2021	Parikshit Gopalan Adam Tauman Kalai Omer Reingold Vatsal Sharan Udi Wieder
+	Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples	2020	Shafi Goldwasser Adam Tauman Kalai Yael Tauman Kalai Omar Montasser
+	Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization.	2020	Vikas Garg Adam Tauman Kalai Katrina Ligett Zhiwei Steven Wu
+	The disparate equilibria of algorithmic decision making when individuals invest rationally	2020	Lydia T. Liu Ashia Wilson Nika Haghtalab Adam Tauman Kalai Christian Borgs Jennifer Chayes
+	Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples	2020	Shafi Goldwasser Adam Tauman Kalai Yael Tauman Kalai Omar Montasser
+	Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization	2020	Vikas Garg Adam Tauman Kalai Katrina Ligett Zhiwei Steven Wu
+	The Disparate Equilibria of Algorithmic Decision Making when Individuals Invest Rationally	2019	Lydia T. Liu Ashia Wilson Nika Haghtalab Adam Tauman Kalai Christian Borgs Jennifer Chayes
+	Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops	2019	Limor Gultchin Geneviève Patterson Nancy K. Baym Nathaniel Swinger Adam Tauman Kalai
+ PDF Chat	What are the Biases in My Word Embedding?	2019	Nathaniel Swinger Maria De‐Arteaga Neil T. Heffernan Mark D.M. Leiserson Adam Tauman Kalai
+ PDF Chat	Bias in Bios	2019	Maria De‐Arteaga Alexey Romanov Hanna Wallach Jennifer Chayes Christian Borgs Alexandra Chouldechova Sahin Cem Geyik Krishnaram Kenthapadi Adam Tauman Kalai
+	What's in a Name? Reducing Bias in Bios without Access to Protected Attributes	2019	Alexey Romanov Maria De‐Arteaga Hanna Wallach Jennifer Chayes Christian Borgs Alexandra Chouldechova Sahin Cem Geyik Krishnaram Kenthapadi Anna Rumshisky Adam Tauman Kalai
+	Learning to Prune: Speeding up Repeated Computations	2019	Daniel Alabi Adam Tauman Kalai Katrina Ligett Cameron Musco Christos Tzamos Ellen Vitercik
+	Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops	2019	Limor Gultchin Geneviève Patterson Nancy K. Baym Nathaniel Swinger Adam Tauman Kalai
+	The Disparate Equilibria of Algorithmic Decision Making when Individuals Invest Rationally	2019	Lydia T. Liu Ashia C. Wilson Nika Haghtalab Adam Tauman Kalai Christian Borgs Jennifer Chayes
+ PDF Chat	Usability of Humanly Computable Passwords	2018	Samira Samadi Santosh Vempala Adam Tauman Kalai
+ PDF Chat	Glass-Box Program Synthesis: A Machine Learning Approach	2018	Konstantina Christakopoulou Adam Tauman Kalai
+	When optimizing nonlinear objectives is no harder than linear objectives.	2018	Daniel Alabi Nicole Immorlica Adam Tauman Kalai
+	Unleashing Linear Optimizers for Group-Fair Learning and Optimization	2018	Daniel Alabi Nicole Immorlica Adam Tauman Kalai
+	Actively Avoiding Nonsense in Generative Models	2018	Steve Hanneke Adam Tauman Kalai Gautam Kamath Christos Tzamos
+	What are the biases in my word embedding?	2018	Nathaniel Swinger Maria De‐Arteaga Neil T. Heffernan Mark D.M. Leiserson Adam Tauman Kalai
+	Unleashing Linear Optimizers for Group-Fair Learning and Optimization	2018	Daniel Alabi Nicole Immorlica Adam Tauman Kalai
+	Decoupled classifiers for fair and efficient machine learning	2017	Cynthia Dwork Nicole Immorlica Adam Tauman Kalai Max Leiserson
+	Decoupled classifiers for fair and efficient machine learning	2017	Cynthia Dwork Nicole Immorlica Adam Tauman Kalai Mark D.M. Leiserson
+	Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context	2017	Shyam Upadhyay Kai-Wei Chang Matt Taddy Adam Tauman Kalai James Zou
+	Supervising Unsupervised Learning	2017	Vikas Garg Adam Tauman Kalai
+	Counterfactual Language Model Adaptation for Suggesting Phrases	2017	Kenneth C. Arnold Kai-Wei Chang Adam Tauman Kalai
+	Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context	2017	Shyam Upadhyay Kai-Wei Chang Matt Taddy Adam Tauman Kalai James Zou
+	Glass-Box Program Synthesis: A Machine Learning Approach	2017	Konstantina Christakopoulou Adam Tauman Kalai
+	Decoupled classifiers for fair and efficient machine learning	2017	Cynthia Dwork Nicole Immorlica Adam Tauman Kalai Max Leiserson
+	Usability of Humanly Computable Passwords	2017	Samira Samadi Santosh Vempala Adam Tauman Kalai
+	Meta-Unsupervised-Learning: A supervised approach to unsupervised learning.	2016	Vikas Garg Adam Tauman Kalai
+	Quantifying and Reducing Stereotypes in Word Embeddings	2016	Tolga Bolukbasi Kai-Wei Chang James Zou Venkatesh Saligrama Adam Tauman Kalai
+	Meta-Unsupervised-Learning: A supervised approach to unsupervised learning	2016	Vikas Garg Adam Tauman Kalai
+	Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings	2016	Tolga Bolukbasi Kai-Wei Chang James Zou Venkatesh Saligrama Adam Tauman Kalai
+ PDF Chat	Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons	2015	James Zou Kamalika Chaudhuri Adam Tauman Kalai
+	Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons	2015	James Zou Kamalika Chaudhuri Adam Tauman Kalai
+	Feature Multi-Selection among Subjective Features	2013	Sivan Sabato Adam Tauman Kalai
+	Textual Features for Programming by Example	2012	Aditya Krishna Menon Omer Tamuz Sumit Gulwani Butler Lampson Adam Tauman Kalai
+	Textual Features for Programming by Example	2012	Aditya Krishna Menon Omer Tamuz Sumit Gulwani Butler Lampson Adam Tauman Kalai
+	Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression	2011	Sham M. Kakade Varun Kanade Ohad Shamir Adam Tauman Kalai
+	Adaptively Learning the Crowd Kernel	2011	Omer Tamuz Ce Liu Serge Belongie Ohad Shamir Adam Tauman Kalai
+	Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression	2011	Sham M. Kakade Adam Tauman Kalai Varun Kanade Ohad Shamir
+	Compression without a common prior: An information-theoretic justification for ambiguity in language	2011	Brendan Juba Adam Tauman Kalai Sanjeev Khanna Madhu Sudan
+	Adaptively Learning the Crowd Kernel	2011	Omer Tamuz Ce Liu Ohad Shamir Adam Tauman Kalai Serge Belongie
+	Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression	2011	Sham M. Kakade Adam Tauman Kalai Varun Kanade Ohad Shamir
+	Dueling Algorithms	2011	Nicole Immorlica Adam Tauman Kalai Brendan Lucier Ankur Moitra Andrew Postlewaite Moshe Tennenholtz
+	Decision trees are PAC-learnable from most product distributions: a smoothed analysis	2008	Adam Tauman Kalai Shang‐Hua Teng
+	Simulated Annealing for Convex Optimization	2006	Adam Tauman Kalai Santosh Vempala
+	Online convex optimization in the bandit setting: gradient descent without a gradient	2004	Abraham D. Flaxman Adam Tauman Kalai H. Brendan McMahan
+ PDF Chat	Generating Random Factored Numbers, Easily	2003	Adam Tauman Kalai
+	Generating random factored numbers, easily	2002	Adam Tauman Kalai
+	Noise-tolerant learning, the parity problem, and the statistical query model	2000	Avrim Blum Adam Tauman Kalai Hal Wasserman
+	Noise-Tolerant Learning, the Parity Problem, and the Statistical Query Model	2000	Avrim Blum Adam Tauman Kalai Hal Wasserman

Common Coauthors

Coauthor	Papers Together
Varun Kanade	10
Nicole Immorlica	7
Maria De‐Arteaga	6
Vikas Garg	6
James Zou	6
Christian Borgs	5
Ohad Shamir	5
Kai-Wei Chang	5
Santosh Vempala	5
Jennifer Chayes	5
Omer Tamuz	4
Lester Mackey	4
Nathaniel Swinger	4
Sham M. Kakade	4
Daniel Alabi	4
Mark D.M. Leiserson	3
Katrina Ligett	3
Nika Haghtalab	3
Cynthia Dwork	3
Lydia T. Liu	3
Shafi Goldwasser	3
Tolga Bolukbasi	2
Neil T. Heffernan	2
Yael Tauman Kalai	2
Sahin Cem Geyik	2
Konstantina Christakopoulou	2
Serge Belongie	2
Limor Gultchin	2
Myra Cheng	2
Samira Samadi	2
Omar Montasser	2
Max Leiserson	2
Zhiwei Steven Wu	2
Geneviève Patterson	2
Tal Schuster	2
Matt Taddy	2
Shyam Upadhyay	2
Nancy K. Baym	2
Hanna Wallach	2
Alexey Romanov	2
Kamalika Chaudhuri	2
Alexandra Chouldechova	2
Butler Lampson	2
Venkatesh Saligrama	2
Christos Tzamos	2
Sumit Gulwani	2
Avrim Blum	2
Hal Wasserman	2
Oleksandr Polozov	2
Krishnaram Kenthapadi	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Fairness through awareness	2012	Cynthia Dwork Moritz Hardt Toniann Pitassi Omer Reingold Richard S. Zemel	7
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	5
+ PDF Chat	Semantics derived automatically from language corpora contain human-like biases	2017	Aylin Caliskan Joanna J. Bryson Arvind Narayanan	5
+	Equality of Opportunity in Supervised Learning	2016	Moritz Hardt Eric Price Nathan Srebro	4
+	Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments	2017	Alexandra Chouldechova	4
+ PDF Chat	Enriching Word Vectors with Subword Information	2017	Piotr Bojanowski Édouard Grave Armand Joulin Tomáš Mikolov	4
+ PDF Chat	Bias in Bios	2019	Maria De‐Arteaga Alexey Romanov Hanna Wallach Jennifer Chayes Christian Borgs Alexandra Chouldechova Sahin Cem Geyik Krishnaram Kenthapadi Adam Tauman Kalai	3
+	Decoupled classifiers for fair and efficient machine learning	2017	Cynthia Dwork Nicole Immorlica Adam Tauman Kalai Mark D.M. Leiserson	3
+	Word embeddings quantify 100 years of gender and ethnic stereotypes	2018	Nikhil Garg Londa Schiebinger Dan Jurafsky James Zou	3
+ PDF Chat	What are the Biases in My Word Embedding?	2019	Nathaniel Swinger Maria De‐Arteaga Neil T. Heffernan Mark D.M. Leiserson Adam Tauman Kalai	3
+	Mitigating Unwanted Biases with Adversarial Learning	2018	Brian Hu Zhang Blake Lemoine Margaret Mitchell	2
+	Long term impact of fair machine learning in sequential decision making: representation disparity and group retention.	2019	Xueru Zhang Mohammad Mahdi Khalili Cem Tekin Mingyan Liu	2
+ PDF Chat	Similarity of Semantic Relations	2006	Peter D. Turney	2
+ PDF Chat	Reducing Gender Bias in Abusive Language Detection	2018	Ji Ho Park Jamin Shin Pascale Fung	2
+ PDF Chat	From Fair Decision Making To Social Equality	2019	Hussein Mouzannar Mesrob I. Ohannessian Nathan Srebro	2
+	Practical Bayesian Optimization of Machine Learning Algorithms	2012	Jasper Snoek Hugo Larochelle Ryan P. Adams	2
+	It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia	2021	Claudia Wagner David García Mohsen Jadidi Markus Strohmaier	2
+	The Measure and Mismeasure of Fairness	2018	Sam Corbett‐Davies Sharad Goel	2
+	A State of the Art of Word Sense Induction: A Way Towards Word Sense Disambiguation for Under-Resourced Languages	2013	Mohammad Nasiruddin	2
+	Advances in Pre-Training Distributed Word Representations	2017	Tomáš Mikolov Édouard Grave Piotr Bojanowski Christian Puhrsch Armand Joulin	2
+	Domain Adaptation: Learning Bounds and Algorithms	2009	Yishay Mansour Mehryar Mohri Afshin Rostamizadeh	2
+	Learning under selective labels in the presence of expert consistency	2018	Maria De‐Arteaga Artur Dubrawski Alexandra Chouldechova	2
+	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	2018	Jacob Devlin Ming‐Wei Chang Kenton Lee Kristina Toutanova	2
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	2
+	Improving Consequential Decision Making under Imperfect Predictions.	2019	Niki Kilbertus Manuel Gomez-Rodriguez Bernhard Schölkopf Krikamol Muandet Isabel Valera	2
+ PDF Chat	Strategic Classification	2016	Moritz Hardt Nimrod Megiddo Christos H. Papadimitriou Mary Wootters	2
+	Equality of Opportunity in Supervised Learning	2016	Moritz Hardt Eric Price Nathan Srebro	2
+	Efficient Estimation of Word Representations in Vector Space	2013	Tomáš Mikolov Kai Chen Greg S. Corrado Jay B. Dean	2
+	The Power of Comparisons for Actively Learning Linear Classifiers	2019	Max Hopkins Daniel M. Kane Shachar Lovett	2
+	Random walks and anO*(n5) volume algorithm for convex bodies	1997	Ravi Kannan L�szl� Lov�sz Mikl�s Simonovits	2
+	Gender Bias in Coreference Resolution	2018	Rachel Rudinger Jason Naradowsky Brian Leonard Benjamin Van Durme	2
+ PDF Chat	The Social Cost of Strategic Classification	2019	Smitha Milli John P. Miller Anca D. Dragan Moritz Hardt	2
+	How algorithmic confounding in recommendation systems increases homogeneity and decreases utility	2018	Allison J. B. Chaney Brandon Stewart Barbara E. Engelhardt	2
+ PDF Chat	Risk bounds for statistical learning	2006	Pascal Massart Élodie Nédélec	2
+	Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness	2017	Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu	2
+ PDF Chat	Isotonic Regression under Lipschitz Constraint	2009	Lana Yeganova W. John Wilbur	2
+	Avoiding Discrimination through Causal Reasoning	2017	Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf	2
+	A Trust Region Strategy for Nonlinear Equality Constrained Optimization	1985	Maria Rosa Celis	2
+ PDF Chat	A Note on Polynomial Solvability of the CDT Problem	2016	Daniel Bienstock	2
+	A Short-term Intervention for Long-term Fairness in the Labor Market	2018	Lily Hu Yiling Chen	2
+	Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space	2014	Arvind Neelakantan Jeevan Shankar Alexandre Passos Andrew McCallum	2
+	Stochastic variational inference	2013	Matthew D. Hoffman David M. Blei Chong Wang John Paisley	2
+	Practical Large-Scale Optimization for Max-norm Regularization	2010	Jason D. Lee Ben Recht Nathan Srebro Joel A. Tropp Ruslan Salakhutdinov	2
+	How to Generate Factored Random Numbers	1988	Eric Bach	2
+ PDF Chat	Optimal Smoothing in Single-Index Models	1993	Wolfgang Karl Härdle Peter Hall Hidehiko Ichimura	2
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	2
+	Breaking Sticks and Ambiguities with Adaptive Skip-gram	2015	Sergey Bartunov Dmitry Kondrashkin Anton Osokin Dmitry Vetrov	2
+	Simulated annealing in convex bodies and an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:msup><mml:mrow><mml:mi>O</mml:mi></mml:mrow><mml:mrow><mml:mo>*</mml:mo></mml:mrow></mml:msup><mml:mo stretchy="false">(</mml:mo><mml:msup><mml:mrow><mml:mi>n</mml:mi></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math> volume algorithm	2005	László Lovász Santosh Vempala	2
+	The Volume of Convex Bodies and Banach Space Geometry	1989	Gilles Pisier	2
+	Online convex programming and generalized infinitesimal gradient ascent	2003	Martin Zinkevich	2